A Vector Representation of Lactation Curves for Dairy Cowsopen access
- Authors
- Lee, S.; Park, J.
- Issue Date
- Mar-2022
- Publisher
- MDPI
- Keywords
- Lactation curve; Piecewise linear regression; Vector representation
- Citation
- Agriculture (Switzerland), v.12, no.3
- Journal Title
- Agriculture (Switzerland)
- Volume
- 12
- Number
- 3
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/57685
- DOI
- 10.3390/agriculture12030395
- ISSN
- 2077-0472
2077-0472
- Abstract
- Machine learning techniques provide efficient data analysis tools without mathematical derivations. Data-centric LC representations are highly demanded to use these tools for LC-related research. A novel data-oriented LC representation model using piecewise linear regression (PWLR) is presented. This representation is intended to be used directly as data for machine learning along with other associated data at an individual base. An LC is represented in vector form as a series of connected line segments and the location and number of segments are determined by the maximum residual. The critical points are determined at the rapid transit point in the LC. The Bayesian information criterion was used to choose the proper number of line segments to avoid the overfitting problem. To demonstrate the validity of the PWLR model as an LC descriptor, its approximation accuracy and representation generality were tested experimentally. The results revealed that the PWLR model is advantageous for representing the LCs of an individual or a large herd that are directly applicable to data-driven approaches.
- Files in This Item
-
- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/57685)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.